Pandas Profiling Report

Dataset statistics

Number of variables	20
Number of observations	176573
Missing cells	176543
Missing cells (%)	5.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	26.9 MiB
Average record size in memory	160.0 B

Variable types

Numeric	8
Categorical	12

Warnings

`batsman` has a high cardinality: 514 distinct values	High cardinality
`bowler` has a high cardinality: 404 distinct values	High cardinality
`non_striker` has a high cardinality: 509 distinct values	High cardinality
`player_out` has a high cardinality: 487 distinct values	High cardinality
`fielder_caught_out` has a high cardinality: 509 distinct values	High cardinality
`id` is highly correlated with `season`	High correlation
`season` is highly correlated with `id`	High correlation
`extras_wides` is highly correlated with `total_extras_runs`	High correlation
`extras_legbyes` is highly correlated with `total_extras_runs`	High correlation
`total_extras_runs` is highly correlated with `extras_wides` and 1 other fields	High correlation
`batsman_runs` is highly correlated with `total_runs`	High correlation
`total_runs` is highly correlated with `batsman_runs`	High correlation
`id` is highly correlated with `season`	High correlation
`season` is highly correlated with `id`	High correlation
`extras_wides` is highly correlated with `total_extras_runs`	High correlation
`extras_legbyes` is highly correlated with `total_extras_runs`	High correlation
`total_extras_runs` is highly correlated with `extras_wides` and 1 other fields	High correlation
`batsman_runs` is highly correlated with `total_runs`	High correlation
`total_runs` is highly correlated with `batsman_runs`	High correlation
`id` is highly correlated with `season`	High correlation
`season` is highly correlated with `id`	High correlation
`extras_wides` is highly correlated with `total_extras_runs`	High correlation
`extras_legbyes` is highly correlated with `total_extras_runs`	High correlation
`total_extras_runs` is highly correlated with `extras_wides` and 1 other fields	High correlation
`batsman_runs` is highly correlated with `total_runs`	High correlation
`total_runs` is highly correlated with `batsman_runs`	High correlation
`total_extras_runs` is highly correlated with `total_runs` and 3 other fields	High correlation
`innings` is highly correlated with `replacements`	High correlation
`bowled_over` is highly correlated with `replacements`	High correlation
`total_runs` is highly correlated with `total_extras_runs` and 3 other fields	High correlation
`type_out` is highly correlated with `replacements`	High correlation
`extras_legbyes` is highly correlated with `total_extras_runs`	High correlation
`season` is highly correlated with `replacements` and 1 other fields	High correlation
`replacements` is highly correlated with `innings` and 7 other fields	High correlation
`extras_penalty` is highly correlated with `total_extras_runs`	High correlation
`batsman_team` is highly correlated with `replacements`	High correlation
`batsman_runs` is highly correlated with `total_runs` and 1 other fields	High correlation
`id` is highly correlated with `season` and 1 other fields	High correlation
`extras_wides` is highly correlated with `total_extras_runs` and 1 other fields	High correlation
`extras_noballs` is highly correlated with `replacements`	High correlation
`replacements` is highly correlated with `extras_noballs` and 5 other fields	High correlation
`extras_byes` is highly correlated with `replacements`	High correlation
`extras_penalty` is highly correlated with `replacements`	High correlation
`batsman_team` is highly correlated with `replacements`	High correlation
`innings` is highly correlated with `replacements`	High correlation
`type_out` is highly correlated with `replacements`	High correlation
`replacements` has 176543 (> 99.9%) missing values	Missing
`replacements` is uniformly distributed	Uniform
`extras_wides` has 171230 (97.0%) zeros	Zeros
`extras_legbyes` has 173664 (98.4%) zeros	Zeros
`total_extras_runs` has 167142 (94.7%) zeros	Zeros
`batsman_runs` has 71130 (40.3%) zeros	Zeros
`total_runs` has 62100 (35.2%) zeros	Zeros

Reproduction

Analysis started	2021-09-17 17:19:35.749448
Analysis finished	2021-09-17 17:20:46.657144
Duration	1 minute and 10.91 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

id
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	746
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	713160.0962

Minimum	335982
Maximum	1178425
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.3 MiB

Quantile statistics

Minimum	335982
5-th percentile	336019
Q1	501208
median	598047
Q3	980985
95-th percentile	1175368
Maximum	1178425
Range	842443
Interquartile range (IQR)	479777

Descriptive statistics

Standard deviation	284366.5362
Coefficient of variation (CV)	0.3987415135
Kurtosis	-1.33600124
Mean	713160.0962
Median Absolute Deviation (MAD)	205835
Skewness	0.3585860896
Sum	1.259248177 × 10¹¹
Variance	8.086432689 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
829737	262	0.1%
829811	259	0.1%
1178423	257	0.1%
419142	257	0.1%
734047	257	0.1%
501221	257	0.1%
548367	256	0.1%
829805	256	0.1%
392190	256	0.1%
829777	255	0.1%
Other values (736)	174001	98.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
335982	225	0.1%
335983	248	0.1%
335984	219	0.1%
335985	246	0.1%
335986	240	0.1%
335987	241	0.1%
335988	205	0.1%
335989	255	0.1%
335990	248	0.1%
335991	250	0.1%

Value	Count	Frequency (%)
1178425	223	0.1%
1178424	51	< 0.1%
1178423	257	0.1%
1178422	246	0.1%
1178421	242	0.1%
1178420	241	0.1%
1178419	235	0.1%
1178418	244	0.1%
1178417	249	0.1%
1178416	244	0.1%

season
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	12
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2013.368386

Minimum	2008
Maximum	2019
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.3 MiB

Quantile statistics

Minimum	2008
5-th percentile	2008
Q1	2011
median	2013
Q3	2016
95-th percentile	2019
Maximum	2019
Range	11
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.323319105
Coefficient of variation (CV)	0.001650626447
Kurtosis	-1.126435923
Mean	2013.368386
Median Absolute Deviation (MAD)	3
Skewness	0.07451207835
Sum	355506496
Variance	11.04444988
Monotonicity	Increasing

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
2013	18152	10.3%
2012	17767	10.1%
2011	17013	9.6%
2010	14489	8.2%
2014	14288	8.1%
2018	14286	8.1%
2016	14096	8.0%
2017	13849	7.8%
2015	13641	7.7%
2009	13595	7.7%
Other values (2)	25397	14.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2008	13489	7.6%
2009	13595	7.7%
2010	14489	8.2%
2011	17013	9.6%
2012	17767	10.1%
2013	18152	10.3%
2014	14288	8.1%
2015	13641	7.7%
2016	14096	8.0%
2017	13849	7.8%

Value	Count	Frequency (%)
2019	11908	6.7%
2018	14286	8.1%
2017	13849	7.8%
2016	14096	8.0%
2015	13641	7.7%
2014	14288	8.1%
2013	18152	10.3%
2012	17767	10.1%
2011	17013	9.6%
2010	14489	8.2%

batsman
Categorical

HIGH CARDINALITY

Distinct	514
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	1.3 MiB

V Kohli	4202
SK Raina	3968
RG Sharma	3732
S Dhawan	3732
G Gambhir	3524
Other values (509)	157415

Length

Max length	23
Median length	9
Mean length	9.347589949
Min length	5

Characters and Unicode

Total characters	1650532
Distinct characters	54
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	13 ?
Unique (%)	< 0.1%

Sample

1st row	AC Gilchrist
2nd row	AC Gilchrist
3rd row	AC Gilchrist
4th row	Y Venugopal Rao
5th row	Y Venugopal Rao

Common Values

Value	Count	Frequency (%)
V Kohli	4202	2.4%
SK Raina	3968	2.2%
RG Sharma	3732	2.1%
S Dhawan	3732	2.1%
G Gambhir	3524	2.0%
RV Uthappa	3422	1.9%
DA Warner	3397	1.9%
MS Dhoni	3260	1.8%
AM Rahane	3208	1.8%
CH Gayle	3073	1.7%
Other values (504)	141055	79.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
v	6418	1.8%
s	6109	1.7%
singh	4851	1.3%
da	4771	1.3%
sharma	4585	1.3%
sr	4557	1.3%
sk	4248	1.2%
de	4242	1.2%
kohli	4222	1.2%
m	4128	1.1%
Other values (706)	313709	86.7%

Most occurring characters

Value	Count	Frequency (%)
	185267	11.2%
a	182402	11.1%
i	80429	4.9%
n	76242	4.6%
h	75624	4.6%
r	71129	4.3%
e	67135	4.1%
S	66529	4.0%
l	62276	3.8%
s	43513	2.6%
Other values (44)	739986	44.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	959376	58.1%
Uppercase Letter	505666	30.6%
Space Separator	185267	11.2%
Dash Punctuation	223	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
S	66529	13.2%
M	43242	8.6%
R	43083	8.5%
A	41503	8.2%
K	40834	8.1%
D	34928	6.9%
P	34447	6.8%
J	24301	4.8%
G	23471	4.6%
V	22872	4.5%
Other values (16)	130456	25.8%

Lowercase Letter

Value	Count	Frequency (%)
a	182402	19.0%
i	80429	8.4%
n	76242	7.9%
h	75624	7.9%
r	71129	7.4%
e	67135	7.0%
l	62276	6.5%
s	43513	4.5%
t	36682	3.8%
o	36490	3.8%
Other values (16)	227454	23.7%

Space Separator

Value	Count	Frequency (%)
	185267	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	223	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1465042	88.8%
Common	185490	11.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	182402	12.5%
i	80429	5.5%
n	76242	5.2%
h	75624	5.2%
r	71129	4.9%
e	67135	4.6%
S	66529	4.5%
l	62276	4.3%
s	43513	3.0%
M	43242	3.0%
Other values (42)	696521	47.5%

Common

Value	Count	Frequency (%)
	185267	99.9%
-	223	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1650532	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	185267	11.2%
a	182402	11.1%
i	80429	4.9%
n	76242	4.6%
h	75624	4.6%
r	71129	4.3%
e	67135	4.1%
S	66529	4.0%
l	62276	3.8%
s	43513	2.6%
Other values (44)	739986	44.8%

bowler
Categorical

HIGH CARDINALITY

Distinct	404
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.3 MiB

Harbhajan Singh	3352
PP Chawla	3133
A Mishra	3100
R Ashwin	2966
SL Malinga	2878
Other values (399)	161144

Length

Max length	23
Median length	9
Mean length	9.535931315
Min length	5

Characters and Unicode

Total characters	1683788
Distinct characters	55
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	GD McGrath
2nd row	GD McGrath
3rd row	GD McGrath
4th row	GD McGrath
5th row	GD McGrath

Common Values

Value	Count	Frequency (%)
Harbhajan Singh	3352	1.9%
PP Chawla	3133	1.8%
A Mishra	3100	1.8%
R Ashwin	2966	1.7%
SL Malinga	2878	1.6%
P Kumar	2637	1.5%
B Kumar	2631	1.5%
DJ Bravo	2620	1.5%
UT Yadav	2571	1.5%
SP Narine	2545	1.4%
Other values (394)	148140	83.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
r	9587	2.7%
singh	9132	2.5%
sharma	9113	2.5%
a	8379	2.3%
kumar	7478	2.1%
s	6076	1.7%
m	5986	1.7%
pp	5078	1.4%
p	4679	1.3%
b	4124	1.1%
Other values (578)	290435	80.7%

Most occurring characters

Value	Count	Frequency (%)
a	214753	12.8%
	183494	10.9%
n	90023	5.3%
r	88641	5.3%
h	86147	5.1%
i	73765	4.4%
e	72562	4.3%
S	66069	3.9%
l	54201	3.2%
M	46001	2.7%
Other values (45)	708132	42.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1026217	60.9%
Uppercase Letter	473371	28.1%
Space Separator	183494	10.9%
Dash Punctuation	631	< 0.1%
Open Punctuation	25	< 0.1%
Decimal Number	25	< 0.1%
Close Punctuation	25	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	214753	20.9%
n	90023	8.8%
r	88641	8.6%
h	86147	8.4%
i	73765	7.2%
e	72562	7.1%
l	54201	5.3%
o	39397	3.8%
t	38891	3.8%
m	38239	3.7%
Other values (16)	229598	22.4%

Uppercase Letter

Value	Count	Frequency (%)
S	66069	14.0%
M	46001	9.7%
A	41757	8.8%
P	40690	8.6%
K	35016	7.4%
R	33168	7.0%
J	30768	6.5%
B	24797	5.2%
D	22003	4.6%
C	19609	4.1%
Other values (14)	113493	24.0%

Space Separator

Value	Count	Frequency (%)
	183494	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	631	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	25	100.0%

Decimal Number

Value	Count	Frequency (%)
2	25	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	25	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1499588	89.1%
Common	184200	10.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	214753	14.3%
n	90023	6.0%
r	88641	5.9%
h	86147	5.7%
i	73765	4.9%
e	72562	4.8%
S	66069	4.4%
l	54201	3.6%
M	46001	3.1%
A	41757	2.8%
Other values (40)	665669	44.4%

Common

Value	Count	Frequency (%)
	183494	99.6%
-	631	0.3%
(	25	< 0.1%
2	25	< 0.1%
)	25	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1683788	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	214753	12.8%
	183494	10.9%
n	90023	5.3%
r	88641	5.3%
h	86147	5.1%
i	73765	4.4%
e	72562	4.3%
S	66069	3.9%
l	54201	3.2%
M	46001	2.7%
Other values (45)	708132	42.1%

innings
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.3 MiB

1st	91487
2nd	85086

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	529719
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1st
2nd row	1st
3rd row	1st
4th row	1st
5th row	1st

Common Values

Value	Count	Frequency (%)
1st	91487	51.8%
2nd	85086	48.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1st	91487	51.8%
2nd	85086	48.2%

Most occurring characters

Value	Count	Frequency (%)
1	91487	17.3%
s	91487	17.3%
t	91487	17.3%
2	85086	16.1%
n	85086	16.1%
d	85086	16.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	353146	66.7%
Decimal Number	176573	33.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
s	91487	25.9%
t	91487	25.9%
n	85086	24.1%
d	85086	24.1%

Decimal Number

Value	Count	Frequency (%)
1	91487	51.8%
2	85086	48.2%

Most occurring scripts

Value	Count	Frequency (%)
Latin	353146	66.7%
Common	176573	33.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
s	91487	25.9%
t	91487	25.9%
n	85086	24.1%
d	85086	24.1%

Common

Value	Count	Frequency (%)
1	91487	51.8%
2	85086	48.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	529719	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	91487	17.3%
s	91487	17.3%
t	91487	17.3%
2	85086	16.1%
n	85086	16.1%
d	85086	16.1%

non_striker
Categorical

HIGH CARDINALITY

Distinct	509
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	1.3 MiB

SK Raina	4092
V Kohli	4061
S Dhawan	4034
RG Sharma	3771
G Gambhir	3740
Other values (504)	156875

Length

Max length	23
Median length	9
Mean length	9.352426475
Min length	5

Characters and Unicode

Total characters	1651386
Distinct characters	54
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	< 0.1%

Sample

1st row	JC Buttler
2nd row	AM Rahane
3rd row	AM Rahane
4th row	AM Rahane
5th row	AM Rahane

Common Values

Value	Count	Frequency (%)
SK Raina	4092	2.3%
V Kohli	4061	2.3%
S Dhawan	4034	2.3%
RG Sharma	3771	2.1%
G Gambhir	3740	2.1%
AM Rahane	3457	2.0%
RV Uthappa	3327	1.9%
DA Warner	3126	1.8%
AB de Villiers	2982	1.7%
CH Gayle	2969	1.7%
Other values (499)	141014	79.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
v	6419	1.8%
s	6288	1.7%
sr	4754	1.3%
sharma	4715	1.3%
singh	4580	1.3%
da	4490	1.2%
sk	4342	1.2%
m	4303	1.2%
de	4193	1.2%
dhawan	4153	1.1%
Other values (704)	313662	86.7%

Most occurring characters

Value	Count	Frequency (%)
	185326	11.2%
a	183607	11.1%
i	80194	4.9%
n	76211	4.6%
h	75407	4.6%
r	71024	4.3%
e	68065	4.1%
S	66503	4.0%
l	61756	3.7%
M	43881	2.7%
Other values (44)	739412	44.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	960341	58.2%
Uppercase Letter	505463	30.6%
Space Separator	185326	11.2%
Dash Punctuation	256	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
S	66503	13.2%
M	43881	8.7%
R	43138	8.5%
A	41355	8.2%
K	40763	8.1%
P	34252	6.8%
D	34162	6.8%
J	24290	4.8%
G	23768	4.7%
V	23073	4.6%
Other values (16)	130278	25.8%

Lowercase Letter

Value	Count	Frequency (%)
a	183607	19.1%
i	80194	8.4%
n	76211	7.9%
h	75407	7.9%
r	71024	7.4%
e	68065	7.1%
l	61756	6.4%
s	43366	4.5%
t	36052	3.8%
o	35218	3.7%
Other values (16)	229441	23.9%

Space Separator

Value	Count	Frequency (%)
	185326	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	256	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1465804	88.8%
Common	185582	11.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	183607	12.5%
i	80194	5.5%
n	76211	5.2%
h	75407	5.1%
r	71024	4.8%
e	68065	4.6%
S	66503	4.5%
l	61756	4.2%
M	43881	3.0%
s	43366	3.0%
Other values (42)	695790	47.5%

Common

Value	Count	Frequency (%)
	185326	99.9%
-	256	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1651386	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	185326	11.2%
a	183607	11.1%
i	80194	4.9%
n	76211	4.6%
h	75407	4.6%
r	71024	4.3%
e	68065	4.1%
S	66503	4.0%
l	61756	3.7%
M	43881	2.7%
Other values (44)	739412	44.8%

replacements
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	30
Distinct (%)	100.0%
Missing	176543
Missing (%)	> 99.9%
Memory size	1.3 MiB

{'role': [{'in': 'Harmeet Singh', 'out': 'RP Singh', 'reason': 'excluded - high full pitched balls', 'role': 'bowler'}]}	1
{'role': [{'in': 'A Ashish Reddy', 'reason': 'injury', 'role': 'bowler'}]}	1
{'role': [{'in': 'Mandeep Singh', 'out': 'AC Gilchrist', 'reason': 'injury', 'role': 'batter'}]}	1
{'role': [{'in': 'AT Rayudu', 'out': 'SR Tendulkar', 'reason': 'injury', 'role': 'batter'}]}	1
{'role': [{'in': 'AD Mascarenhas', 'out': 'Kamran Khan', 'reason': 'injury', 'role': 'bowler'}]}	1
Other values (25)	25

Length

Max length	124
Median length	88.5
Mean length	87.9
Min length	66

Characters and Unicode

Total characters	2637
Distinct characters	52
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	30 ?
Unique (%)	100.0%

Sample

1st row	{'role': [{'in': 'RG Sharma', 'reason': 'injury', 'role': 'bowler'}]}
2nd row	{'role': [{'in': 'PP Chawla', 'reason': 'injury', 'role': 'bowler'}]}
3rd row	{'role': [{'in': 'Bipul Sharma', 'out': 'Harmeet Singh', 'reason': 'excluded - high full pitched balls', 'role': 'bowler'}]}
4th row	{'role': [{'in': 'BCJ Cutting', 'reason': 'injury', 'role': 'bowler'}]}
5th row	{'role': [{'in': 'N Rana', 'reason': 'injury', 'role': 'bowler'}]}

Common Values

Value	Count	Frequency (%)
{'role': [{'in': 'Harmeet Singh', 'out': 'RP Singh', 'reason': 'excluded - high full pitched balls', 'role': 'bowler'}]}	1	< 0.1%
{'role': [{'in': 'A Ashish Reddy', 'reason': 'injury', 'role': 'bowler'}]}	1	< 0.1%
{'role': [{'in': 'Mandeep Singh', 'out': 'AC Gilchrist', 'reason': 'injury', 'role': 'batter'}]}	1	< 0.1%
{'role': [{'in': 'AT Rayudu', 'out': 'SR Tendulkar', 'reason': 'injury', 'role': 'batter'}]}	1	< 0.1%
{'role': [{'in': 'AD Mascarenhas', 'out': 'Kamran Khan', 'reason': 'injury', 'role': 'bowler'}]}	1	< 0.1%
{'role': [{'in': 'MC Henriques', 'reason': 'injury', 'role': 'bowler'}]}	1	< 0.1%
{'role': [{'in': 'R Ashwin', 'out': 'Mujeeb Ur Rahman', 'reason': 'injury', 'role': 'bowler'}]}	1	< 0.1%
{'role': [{'in': 'AB de Villiers', 'out': 'SS Tiwary', 'reason': 'injury', 'role': 'batter'}]}	1	< 0.1%
{'role': [{'in': 'Harbhajan Singh', 'out': 'DL Chahar', 'reason': 'injury', 'role': 'bowler'}]}	1	< 0.1%
{'role': [{'in': 'SK Raina', 'reason': 'injury', 'role': 'bowler'}]}	1	< 0.1%
Other values (20)	20	< 0.1%
(Missing)	176543	> 99.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
role	60	18.6%
reason	30	9.3%
in	30	9.3%
bowler	24	7.4%
injury	23	7.1%
out	15	4.6%
singh	8	2.5%
	7	2.2%
pitched	7	2.2%
excluded	7	2.2%
Other values (76)	112	34.7%

Most occurring characters

Value	Count	Frequency (%)
'	480	18.2%
	293	11.1%
r	167	6.3%
e	160	6.1%
o	139	5.3%
l	136	5.2%
:	135	5.1%
n	112	4.2%
a	100	3.8%
i	95	3.6%
Other values (42)	820	31.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1345	51.0%
Other Punctuation	690	26.2%
Space Separator	293	11.1%
Uppercase Letter	122	4.6%
Open Punctuation	90	3.4%
Close Punctuation	90	3.4%
Dash Punctuation	7	0.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	167	12.4%
e	160	11.9%
o	139	10.3%
l	136	10.1%
n	112	8.3%
a	100	7.4%
i	95	7.1%
u	61	4.5%
h	50	3.7%
s	49	3.6%
Other values (15)	276	20.5%

Uppercase Letter

Value	Count	Frequency (%)
S	22	18.0%
K	12	9.8%
R	11	9.0%
C	10	8.2%
A	10	8.2%
M	10	8.2%
P	7	5.7%
J	7	5.7%
H	6	4.9%
D	6	4.9%
Other values (8)	21	17.2%

Other Punctuation

Value	Count	Frequency (%)
'	480	69.6%
:	135	19.6%
,	75	10.9%

Open Punctuation

Value	Count	Frequency (%)
{	60	66.7%
[	30	33.3%

Close Punctuation

Value	Count	Frequency (%)
}	60	66.7%
]	30	33.3%

Space Separator

Value	Count	Frequency (%)
	293	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	7	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1467	55.6%
Common	1170	44.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	167	11.4%
e	160	10.9%
o	139	9.5%
l	136	9.3%
n	112	7.6%
a	100	6.8%
i	95	6.5%
u	61	4.2%
h	50	3.4%
s	49	3.3%
Other values (33)	398	27.1%

Common

Value	Count	Frequency (%)
'	480	41.0%
	293	25.0%
:	135	11.5%
,	75	6.4%
{	60	5.1%
}	60	5.1%
[	30	2.6%
]	30	2.6%
-	7	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2637	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
'	480	18.2%
	293	11.1%
r	167	6.3%
e	160	6.1%
o	139	5.3%
l	136	5.2%
:	135	5.1%
n	112	4.2%
a	100	3.8%
i	95	3.6%
Other values (42)	820	31.1%

bowled_over
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	180
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9.528801685

Minimum	0.1
Maximum	19.9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.3 MiB

Quantile statistics

Minimum	0.1
5-th percentile	0.6
Q1	4.5
median	9.4
Q3	14.4
95-th percentile	18.5
Maximum	19.9
Range	19.8
Interquartile range (IQR)	9.9

Descriptive statistics

Standard deviation	5.677219708
Coefficient of variation (CV)	0.5957957669
Kurtosis	-1.180961644
Mean	9.528801685
Median Absolute Deviation (MAD)	4.9
Skewness	0.04965397921
Sum	1682529.1
Variance	32.23082361
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1.1	1491	0.8%
0.6	1490	0.8%
0.1	1490	0.8%
0.2	1490	0.8%
3.1	1490	0.8%
2.1	1490	0.8%
0.3	1490	0.8%
0.5	1490	0.8%
0.4	1490	0.8%
1.3	1489	0.8%
Other values (170)	161673	91.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.1	1490	0.8%
0.2	1490	0.8%
0.3	1490	0.8%
0.4	1490	0.8%
0.5	1490	0.8%
0.6	1490	0.8%
0.7	364	0.2%
0.8	64	< 0.1%
0.9	13	< 0.1%
1.1	1491	0.8%

Value	Count	Frequency (%)
19.9	5	< 0.1%
19.8	35	< 0.1%
19.7	239	0.1%
19.6	969	0.5%
19.5	1017	0.6%
19.4	1052	0.6%
19.3	1079	0.6%
19.2	1114	0.6%
19.1	1142	0.6%
18.9	11	< 0.1%

batsman_team
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	15
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.3 MiB

Mumbai Indians	22149
Royal Challengers Bangalore	20770
Kings XI Punjab	20684
Kolkata Knight Riders	20592
Chennai Super Kings	19271
Other values (10)	73107

Length

Max length	27
Median length	16
Mean length	17.99051384
Min length	13

Characters and Unicode

Total characters	3176639
Distinct characters	37
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Rajasthan Royals
2nd row	Rajasthan Royals
3rd row	Rajasthan Royals
4th row	Rajasthan Royals
5th row	Rajasthan Royals

Common Values

Value	Count	Frequency (%)
Mumbai Indians	22149	12.5%
Royal Challengers Bangalore	20770	11.8%
Kings XI Punjab	20684	11.7%
Kolkata Knight Riders	20592	11.7%
Chennai Super Kings	19271	10.9%
Delhi Daredevils	18780	10.6%
Rajasthan Royals	17147	9.7%
Sunrisers Hyderabad	12525	7.1%
Deccan Chargers	9034	5.1%
Pune Warriors	5443	3.1%
Other values (5)	10178	5.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
kings	39955	9.1%
indians	22149	5.0%
mumbai	22149	5.0%
royal	20770	4.7%
challengers	20770	4.7%
bangalore	20770	4.7%
punjab	20684	4.7%
xi	20684	4.7%
kolkata	20592	4.7%
knight	20592	4.7%
Other values (22)	210410	47.9%

Most occurring characters

Value	Count	Frequency (%)
a	361322	11.4%
n	263758	8.3%
	262952	8.3%
e	238027	7.5%
i	218932	6.9%
s	209407	6.6%
r	182357	5.7%
l	163077	5.1%
g	118081	3.7%
h	108734	3.4%
Other values (27)	1049992	33.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2453478	77.2%
Uppercase Letter	460209	14.5%
Space Separator	262952	8.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	361322	14.7%
n	263758	10.8%
e	238027	9.7%
i	218932	8.9%
s	209407	8.5%
r	182357	7.4%
l	163077	6.6%
g	118081	4.8%
h	108734	4.4%
u	92172	3.8%
Other values (11)	497611	20.3%

Uppercase Letter

Value	Count	Frequency (%)
K	84303	18.3%
R	79136	17.2%
C	50633	11.0%
D	48152	10.5%
I	42833	9.3%
S	35276	7.7%
P	29607	6.4%
M	22149	4.8%
B	20770	4.5%
X	20684	4.5%
Other values (5)	26666	5.8%

Space Separator

Value	Count	Frequency (%)
	262952	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2913687	91.7%
Common	262952	8.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	361322	12.4%
n	263758	9.1%
e	238027	8.2%
i	218932	7.5%
s	209407	7.2%
r	182357	6.3%
l	163077	5.6%
g	118081	4.1%
h	108734	3.7%
u	92172	3.2%
Other values (26)	957820	32.9%

Common

Value	Count	Frequency (%)
	262952	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3176639	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	361322	11.4%
n	263758	8.3%
	262952	8.3%
e	238027	7.5%
i	218932	6.9%
s	209407	6.6%
r	182357	5.7%
l	163077	5.1%
g	118081	3.7%
h	108734	3.4%
Other values (27)	1049992	33.1%

player_out
Categorical

HIGH CARDINALITY

Distinct	487
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	1.3 MiB

0	167862
SK Raina	157
RG Sharma	152
RV Uthappa	151
V Kohli	142
Other values (482)	8109

Length

Max length	23
Median length	1
Mean length	1.413789198
Min length	1

Characters and Unicode

Total characters	249637
Distinct characters	55
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	84 ?
Unique (%)	< 0.1%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	167862	95.1%
SK Raina	157	0.1%
RG Sharma	152	0.1%
RV Uthappa	151	0.1%
V Kohli	142	0.1%
G Gambhir	136	0.1%
S Dhawan	135	0.1%
KD Karthik	134	0.1%
PA Patel	125	0.1%
AM Rahane	115	0.1%
Other values (477)	7464	4.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
0	167862	90.4%
singh	314	0.2%
s	275	0.1%
v	257	0.1%
r	235	0.1%
sharma	233	0.1%
m	223	0.1%
patel	186	0.1%
sk	184	0.1%
sr	180	0.1%
Other values (671)	15754	8.5%

Most occurring characters

Value	Count	Frequency (%)
0	167862	67.2%
a	9294	3.7%
	9130	3.7%
i	3907	1.6%
h	3858	1.5%
n	3789	1.5%
r	3588	1.4%
e	3307	1.3%
S	3223	1.3%
l	2932	1.2%
Other values (45)	38747	15.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	167862	67.2%
Lowercase Letter	47864	19.2%
Uppercase Letter	24758	9.9%
Space Separator	9130	3.7%
Dash Punctuation	23	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
S	3223	13.0%
M	2142	8.7%
A	2111	8.5%
R	2076	8.4%
K	1926	7.8%
P	1803	7.3%
D	1545	6.2%
J	1252	5.1%
V	1074	4.3%
G	1063	4.3%
Other values (16)	6543	26.4%

Lowercase Letter

Value	Count	Frequency (%)
a	9294	19.4%
i	3907	8.2%
h	3858	8.1%
n	3789	7.9%
r	3588	7.5%
e	3307	6.9%
l	2932	6.1%
s	2033	4.2%
t	1891	4.0%
o	1825	3.8%
Other values (16)	11440	23.9%

Decimal Number

Value	Count	Frequency (%)
0	167862	100.0%

Space Separator

Value	Count	Frequency (%)
	9130	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	23	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	177015	70.9%
Latin	72622	29.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	9294	12.8%
i	3907	5.4%
h	3858	5.3%
n	3789	5.2%
r	3588	4.9%
e	3307	4.6%
S	3223	4.4%
l	2932	4.0%
M	2142	2.9%
A	2111	2.9%
Other values (42)	34471	47.5%

Common

Value	Count	Frequency (%)
0	167862	94.8%
	9130	5.2%
-	23	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	249637	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	167862	67.2%
a	9294	3.7%
	9130	3.7%
i	3907	1.6%
h	3858	1.5%
n	3789	1.5%
r	3588	1.4%
e	3307	1.3%
S	3223	1.3%
l	2932	1.2%
Other values (45)	38747	15.5%

fielder_caught_out
Categorical

HIGH CARDINALITY

Distinct	509
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	1.3 MiB

0	170319
MS Dhoni	152
KD Karthik	151
RV Uthappa	123
AB de Villiers	113
Other values (504)	5715

Length

Max length	23
Median length	1
Mean length	1.302135661
Min length	1

Characters and Unicode

Total characters	229922
Distinct characters	56
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	97 ?
Unique (%)	0.1%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	170319	96.5%
MS Dhoni	152	0.1%
KD Karthik	151	0.1%
RV Uthappa	123	0.1%
AB de Villiers	113	0.1%
SK Raina	110	0.1%
PA Patel	95	0.1%
RG Sharma	90	0.1%
V Kohli	86	< 0.1%
NV Ojha	82	< 0.1%
Other values (499)	5252	3.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
0	170319	92.9%
singh	201	0.1%
r	193	0.1%
ms	187	0.1%
m	185	0.1%
sharma	181	0.1%
karthik	165	0.1%
de	160	0.1%
s	158	0.1%
patel	158	0.1%
Other values (632)	11364	6.2%

Most occurring characters

Value	Count	Frequency (%)
0	170319	74.1%
a	6773	2.9%
	6698	2.9%
i	2973	1.3%
h	2908	1.3%
n	2648	1.2%
r	2633	1.1%
e	2352	1.0%
S	2273	1.0%
l	2107	0.9%
Other values (46)	28238	12.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	170319	74.1%
Lowercase Letter	34975	15.2%
Uppercase Letter	17711	7.7%
Space Separator	6698	2.9%
Open Punctuation	102	< 0.1%
Close Punctuation	102	< 0.1%
Dash Punctuation	15	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	6773	19.4%
i	2973	8.5%
h	2908	8.3%
n	2648	7.6%
r	2633	7.5%
e	2352	6.7%
l	2107	6.0%
t	1519	4.3%
s	1509	4.3%
o	1368	3.9%
Other values (16)	8185	23.4%

Uppercase Letter

Value	Count	Frequency (%)
S	2273	12.8%
M	1556	8.8%
K	1555	8.8%
A	1493	8.4%
R	1439	8.1%
P	1332	7.5%
D	1227	6.9%
J	899	5.1%
B	834	4.7%
V	769	4.3%
Other values (15)	4334	24.5%

Decimal Number

Value	Count	Frequency (%)
0	170319	100.0%

Space Separator

Value	Count	Frequency (%)
	6698	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	102	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	102	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	15	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	177236	77.1%
Latin	52686	22.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	6773	12.9%
i	2973	5.6%
h	2908	5.5%
n	2648	5.0%
r	2633	5.0%
e	2352	4.5%
S	2273	4.3%
l	2107	4.0%
M	1556	3.0%
K	1555	3.0%
Other values (41)	24908	47.3%

Common

Value	Count	Frequency (%)
0	170319	96.1%
	6698	3.8%
(	102	0.1%
)	102	0.1%
-	15	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	229922	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	170319	74.1%
a	6773	2.9%
	6698	2.9%
i	2973	1.3%
h	2908	1.3%
n	2648	1.2%
r	2633	1.1%
e	2352	1.0%
S	2273	1.0%
l	2107	0.9%
Other values (46)	28238	12.3%

type_out
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.3 MiB

0	167862
caught	5219
bowled	1566
run out	844
lbw	530
Other values (5)	552

Length

Max length	21
Median length	1
Mean length	1.260288946
Min length	1

Characters and Unicode

Total characters	222533
Distinct characters	22
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	167862	95.1%
caught	5219	3.0%
bowled	1566	0.9%
run out	844	0.5%
lbw	530	0.3%
stumped	280	0.2%
caught and bowled	250	0.1%
retired hurt	11	< 0.1%
hit wicket	10	< 0.1%
obstructing the field	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	167862	94.3%
caught	5469	3.1%
bowled	1816	1.0%
out	844	0.5%
run	844	0.5%
lbw	530	0.3%
stumped	280	0.2%
and	250	0.1%
hurt	11	< 0.1%
retired	11	< 0.1%
Other values (5)	23	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	167862	75.4%
u	7449	3.3%
t	6638	3.0%
a	5719	2.6%
h	5491	2.5%
c	5480	2.5%
g	5470	2.5%
o	2661	1.2%
d	2358	1.1%
w	2356	1.1%
Other values (12)	11049	5.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	167862	75.4%
Lowercase Letter	53304	24.0%
Space Separator	1367	0.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
u	7449	14.0%
t	6638	12.5%
a	5719	10.7%
h	5491	10.3%
c	5480	10.3%
g	5470	10.3%
o	2661	5.0%
d	2358	4.4%
w	2356	4.4%
l	2347	4.4%
Other values (10)	7335	13.8%

Decimal Number

Value	Count	Frequency (%)
0	167862	100.0%

Space Separator

Value	Count	Frequency (%)
	1367	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	169229	76.0%
Latin	53304	24.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
u	7449	14.0%
t	6638	12.5%
a	5719	10.7%
h	5491	10.3%
c	5480	10.3%
g	5470	10.3%
o	2661	5.0%
d	2358	4.4%
w	2356	4.4%
l	2347	4.4%
Other values (10)	7335	13.8%

Common

Value	Count	Frequency (%)
0	167862	99.2%
	1367	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	222533	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	167862	75.4%
u	7449	3.3%
t	6638	3.0%
a	5719	2.6%
h	5491	2.5%
c	5480	2.5%
g	5470	2.5%
o	2661	1.2%
d	2358	1.1%
w	2356	1.1%
Other values (12)	11049	5.0%

extras_wides
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.03682329688

Minimum	0
Maximum	5
Zeros	171230
Zeros (%)	97.0%
Negative	0
Negative (%)	0.0%
Memory size	1.3 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	5
Range	5
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.2516125522
Coefficient of variation (CV)	6.832971881
Kurtosis	191.5014881
Mean	0.03682329688
Median Absolute Deviation (MAD)	0
Skewness	11.65890837
Sum	6502
Variance	0.0633088764
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	171230	97.0%
1	4858	2.8%
2	229	0.1%
5	207	0.1%
3	45	< 0.1%
4	4	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	171230	97.0%
1	4858	2.8%
2	229	0.1%
3	45	< 0.1%
4	4	< 0.1%
5	207	0.1%

Value	Count	Frequency (%)
5	207	0.1%
4	4	< 0.1%
3	45	< 0.1%
2	229	0.1%
1	4858	2.8%
0	171230	97.0%

extras_legbyes
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.02119803141

Minimum	0
Maximum	5
Zeros	173664
Zeros (%)	98.4%
Negative	0
Negative (%)	0.0%
Memory size	1.3 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	5
Range	5
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.1949347214
Coefficient of variation (CV)	9.195887942
Kurtosis	241.5230135
Mean	0.02119803141
Median Absolute Deviation (MAD)	0
Skewness	13.74586003
Sum	3743
Variance	0.03799954562
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	173664	98.4%
1	2536	1.4%
4	216	0.1%
2	136	0.1%
3	17	< 0.1%
5	4	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	173664	98.4%
1	2536	1.4%
2	136	0.1%
3	17	< 0.1%
4	216	0.1%
5	4	< 0.1%

Value	Count	Frequency (%)
5	4	< 0.1%
4	216	0.1%
3	17	< 0.1%
2	136	0.1%
1	2536	1.4%
0	173664	98.4%

extras_noballs
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.3 MiB

0	175870
1	687
2	9
5	6
3	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	176573
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	175870	99.6%
1	687	0.4%
2	9	< 0.1%
5	6	< 0.1%
3	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	175870	99.6%
1	687	0.4%
2	9	< 0.1%
5	6	< 0.1%
3	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	175870	99.6%
1	687	0.4%
2	9	< 0.1%
5	6	< 0.1%
3	1	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	176573	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	175870	99.6%
1	687	0.4%
2	9	< 0.1%
5	6	< 0.1%
3	1	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	176573	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	175870	99.6%
1	687	0.4%
2	9	< 0.1%
5	6	< 0.1%
3	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	176573	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	175870	99.6%
1	687	0.4%
2	9	< 0.1%
5	6	< 0.1%
3	1	< 0.1%

extras_byes
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.3 MiB

0	176097
1	321
4	121
2	31
3	3

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	176573
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	176097	99.7%
1	321	0.2%
4	121	0.1%
2	31	< 0.1%
3	3	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	176097	99.7%
1	321	0.2%
4	121	0.1%
2	31	< 0.1%
3	3	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	176097	99.7%
1	321	0.2%
4	121	0.1%
2	31	< 0.1%
3	3	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	176573	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	176097	99.7%
1	321	0.2%
4	121	0.1%
2	31	< 0.1%
3	3	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	176573	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	176097	99.7%
1	321	0.2%
4	121	0.1%
2	31	< 0.1%
3	3	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	176573	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	176097	99.7%
1	321	0.2%
4	121	0.1%
2	31	< 0.1%
3	3	< 0.1%

extras_penalty
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.3 MiB

0	176571
5	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	176573
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	176571	> 99.9%
5	2	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	176571	> 99.9%
5	2	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	176571	> 99.9%
5	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	176573	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	176571	> 99.9%
5	2	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	176573	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	176571	> 99.9%
5	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	176573	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	176571	> 99.9%
5	2	< 0.1%

total_extras_runs
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.06721865744

Minimum	0
Maximum	7
Zeros	167142
Zeros (%)	94.7%
Negative	0
Negative (%)	0.0%
Memory size	1.3 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	7
Range	7
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.3430137251
Coefficient of variation (CV)	5.102954122
Kurtosis	91.09801952
Mean	0.06721865744
Median Absolute Deviation (MAD)	0
Skewness	8.226940401
Sum	11869
Variance	0.1176584156
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
0	167142	94.7%
1	8401	4.8%
2	404	0.2%
4	342	0.2%
5	218	0.1%
3	65	< 0.1%
7	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	167142	94.7%
1	8401	4.8%
2	404	0.2%
3	65	< 0.1%
4	342	0.2%
5	218	0.1%
7	1	< 0.1%

Value	Count	Frequency (%)
7	1	< 0.1%
5	218	0.1%
4	342	0.2%
3	65	< 0.1%
2	404	0.2%
1	8401	4.8%
0	167142	94.7%

batsman_runs
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.237431544

Minimum	0
Maximum	6
Zeros	71130
Zeros (%)	40.3%
Negative	0
Negative (%)	0.0%
Memory size	1.3 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	1
95-th percentile	4
Maximum	6
Range	6
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.609116193
Coefficient of variation (CV)	1.300367847
Kurtosis	1.638279999
Mean	1.237431544
Median Absolute Deviation (MAD)	1
Skewness	1.585889292
Sum	218497
Variance	2.589254921
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
0	71130	40.3%
1	65416	37.0%
4	20075	11.4%
2	11292	6.4%
6	8035	4.6%
3	569	0.3%
5	56	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	71130	40.3%
1	65416	37.0%
2	11292	6.4%
3	569	0.3%
4	20075	11.4%
5	56	< 0.1%
6	8035	4.6%

Value	Count	Frequency (%)
6	8035	4.6%
5	56	< 0.1%
4	20075	11.4%
3	569	0.3%
2	11292	6.4%
1	65416	37.0%
0	71130	40.3%

total_runs
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	8
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.304650201

Minimum	0
Maximum	7
Zeros	62100
Zeros (%)	35.2%
Negative	0
Negative (%)	0.0%
Memory size	1.3 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	1
95-th percentile	4
Maximum	7
Range	7
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.597156266
Coefficient of variation (CV)	1.224202675
Kurtosis	1.579171701
Mean	1.304650201
Median Absolute Deviation (MAD)	1
Skewness	1.555697515
Sum	230366
Variance	2.550908138
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
1	73180	41.4%
0	62100	35.2%
4	20337	11.5%
2	11894	6.7%
6	7988	4.5%
3	672	0.4%
5	354	0.2%
7	48	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	62100	35.2%
1	73180	41.4%
2	11894	6.7%
3	672	0.4%
4	20337	11.5%
5	354	0.2%
6	7988	4.5%
7	48	< 0.1%

Value	Count	Frequency (%)
7	48	< 0.1%
6	7988	4.5%
5	354	0.2%
4	20337	11.5%
3	672	0.4%
2	11894	6.7%
1	73180	41.4%
0	62100	35.2%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	id	season	batsman	bowler	innings	non_striker	replacements	bowled_over	batsman_team	extras_legbyes	total_extras_runs	batsman_runs	total_runs
0	335988	2008	AC Gilchrist	GD McGrath	1st	JC Buttler	NaN	0.1	Rajasthan Royals	1	1	0	1
1	335988	2008	AC Gilchrist	GD McGrath	1st	AM Rahane	NaN	0.2	Rajasthan Royals	0	0	0	0
2	335988	2008	AC Gilchrist	GD McGrath	1st	AM Rahane	NaN	0.3	Rajasthan Royals	0	0	4	4
3	335988	2008	Y Venugopal Rao	GD McGrath	1st	AM Rahane	NaN	0.4	Rajasthan Royals	0	0	0	0
4	335988	2008	Y Venugopal Rao	GD McGrath	1st	AM Rahane	NaN	0.5	Rajasthan Royals	0	0	6	6
5	335988	2008	Y Venugopal Rao	GD McGrath	1st	AM Rahane	NaN	0.6	Rajasthan Royals	0	0	0	0
6	335988	2008	AC Gilchrist	Mohammad Asif	1st	JC Buttler	NaN	1.1	Rajasthan Royals	0	0	0	0
7	335988	2008	AC Gilchrist	Mohammad Asif	1st	JC Buttler	NaN	1.2	Rajasthan Royals	0	0	0	0
8	335988	2008	AC Gilchrist	Mohammad Asif	1st	JC Buttler	NaN	1.3	Rajasthan Royals	0	0	4	4
9	335988	2008	AC Gilchrist	Mohammad Asif	1st	JC Buttler	NaN	1.4	Rajasthan Royals	0	0	4	4

Last rows

	id	season	batsman	bowler	innings	non_striker	replacements	bowled_over	batsman_team	player_out	type_out	batsman_runs	total_runs
176563	1178424	2019	LS Livingstone	NA Saini	2nd	MS Dhoni	NaN	18.3	Chennai Super Kings	0	0	1	1
176564	1178424	2019	LS Livingstone	NA Saini	2nd	SW Billings	NaN	18.4	Chennai Super Kings	0	0	0	0
176565	1178424	2019	SV Samson	K Khejroliya	2nd	SW Billings	NaN	18.5	Chennai Super Kings	0	0	2	2
176566	1178424	2019	SV Samson	K Khejroliya	2nd	SW Billings	NaN	18.6	Chennai Super Kings	0	0	4	4
176567	1178424	2019	LS Livingstone	K Khejroliya	2nd	MS Dhoni	NaN	19.1	Chennai Super Kings	0	0	4	4
176568	1178424	2019	SV Samson	K Khejroliya	2nd	MS Dhoni	NaN	19.2	Chennai Super Kings	0	0	4	4
176569	1178424	2019	SV Samson	K Khejroliya	2nd	MS Dhoni	NaN	19.3	Chennai Super Kings	0	0	2	2
176570	1178424	2019	SV Samson	K Khejroliya	2nd	MS Dhoni	NaN	19.4	Chennai Super Kings	SW Billings	run out	0	0
176571	1178424	2019	LS Livingstone	YS Chahal	2nd	MS Dhoni	NaN	19.5	Chennai Super Kings	0	0	1	1
176572	1178424	2019	SV Samson	YS Chahal	2nd	DJ Bravo	NaN	19.6	Chennai Super Kings	0	0	1	1

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Lowercase Letter

Space Separator

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Dash Punctuation

Open Punctuation

Decimal Number

Close Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Decimal Number

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Lowercase Letter

Space Separator

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Other Punctuation

Open Punctuation

Close Punctuation

Space Separator

Dash Punctuation